Melola Discovery

← Melola Discovery

Open access Jurnal SINTA 1

Resource aware wind farm and D-STATCOM optimal sizing and placement in a distribution power system

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 11 No. 6 (2021)

DOI
10.11591/ijece.v11i6.pp4641-4648
ISSN
2722-2578, 2088-8708
Published
2021-12-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Doubly fed induction generators (DFIG) based wind farms are capable of providing reactive power compensation. Compensation capability enhancement using reactors such as distributed static synchronous compensator (D-STATCOM) while connecting distribution generation (DG) systems to grid is imperative. This paper presents an optimal placement and sizing of offshore wind farms in a coastal distribution system that is emulated on an IEEE 33 bus system. A multi-objective formulation for optimal placement and sizing of the offshore wind farms with both the location and size constraints is developed. Teaching learning algorithm is used to optimize the multi-objective function constraining on the capacity and location of the offshore wind farms. The proposed formulation is a multi-objective problem for placement of the wind generator in the power system with dynamic wind supply to the power system. The random wind speed is generated as the input and the wind farm output generated to perform the optimal sizing and placement in the distributed system. MATLAB based simulation developed is found to be efficient and robust.

Collaboration network of the authors

2 authors · 1 co-authorship link

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Acharya Institute of Technology
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Resource aware wind farm and D-STATCOM optimal sizing and placement in a distribution power system</dc:title><dc:creator>Ansari, Anzum</dc:creator><dc:creator>Byalihal, Shankarlingappa C.</dc:creator><dc:description>&lt;jats:p&gt;&amp;lt;span lang="EN-US"&amp;gt;Doubly fed induction generators (DFIG) based wind farms are capable of providing reactive power compensation. Compensation capability enhancement using reactors such as distributed static synchronous compensator (D-STATCOM) while connecting distribution generation (DG) systems to grid is imperative. This paper presents an optimal placement and sizing of offshore wind farms in a coastal distribution system that is emulated on an IEEE 33 bus system. A multi-objective formulation for optimal placement and sizing of the offshore wind farms with both the location and size constraints is developed. Teaching learning algorithm is used to optimize the multi-objective function constraining on the capacity and location of the offshore wind farms. The proposed formulation is a multi-objective problem for placement of the wind generator in the power system with dynamic wind supply to the power system. The random wind speed is generated as the input and the wind farm output generated to perform the optimal sizing and placement in the distributed system. MATLAB based simulation developed is found to be efficient and robust.&amp;lt;/span&amp;gt;&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2021-12-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v11i6.pp4641-4648</dc:identifier><dc:identifier>10.11591/ijece.v11i6.pp4641-4648</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 11 No 6 (2021); 4641</dc:source><dc:source>2722-2578</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/23982/15212</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>